Recurrence and metastasis of lung cancer demonstrate decreased diffusion on diffusion-weighted magnetic resonance imaging

Amide Proton Transfer-Weighted Imaging and Multiple Models Intravoxel Incoherent Motion-Based 18F-FDG PET/MRI for Predicting Progression-Free Survival in Non-Small Cell Lung Cancer

BACKGROUND

Amide proton transfer-weighted imaging (APTWI) and multiple models intravoxel incoherent motion (IVIM) based 18F-FDG PET/MR could reflect the microscopic information of the tumor from multiple perspectives. However, its value in the prognostic assessment of non-small cell lung cancer (NSCLC) still needs to be further explored.

PURPOSE

To determine whether pretreatment APTWI, mono-, bi-, and stretched-exponential model IVIM, and 18F-FDG PET-derived parameters of the primary lesion may be associated with progression-free survival (PFS) in NSCLC.

STUDY TYPE

Prospective.

POPULATION

Seventy-seven patients (mean age, 62 years, range, 20-81 years) with 37 men and 40 women were included.

FIELD STRENGTH/SEQUENCE

3.0 T 18F-FDG PET/MRI, single shot echo planar imaging sequences for IVIM and fast spin-echo sequences with magnetization transfer pulses for APTWI.

ASSESSMENT

Patient clinical characteristics (age, sex, smoke, subtype, TNM stage, and surgery), PFS (chest CT every 3 months, median follow-up was 18 months, range, 4-27 months), and APTWI (MTRasym(3.5 ppm)), IVIM (ADCstand, D, D*, f, DDC, and α), and 18F-FDG PET (SUVmax, MTV, and TLG) parameters were recorded.

STATISTICAL TESTS

Proportional hazards model, concordance index, calibration curve, decision curve analysis (DCA), and Log-rank test. A P value <0.05 was considered statistically significant.

RESULTS

Histological subtype, TNM stage, MTV, D*, and MTRasym(3.5 ppm) were all independent predictors of PFS. A prediction model based on these predictors was developed with a C-index of 0.895 (95% CI: 0.839-0.951), which was significantly superior to each of the above predictors alone (C-index = 0.629, 0.707, 0.692, 0.678, and 0.558, respectively). The calibration curve and DCA indicated good consistency and clinical utility of the prediction model, respectively. Log-rank test results showed a significant difference in PFS between the high- and low-risk groups.

DATA CONCLUSION

APTWI and multiple models IVIM based 18F-FDG PET/MRI can be used for PFS assessment in NSCLC.

EVIDENCE LEVEL

3 TECHNICAL EFFICACY: Stage 2.

The microbiome types of colorectal tissue are potentially associated with the prognosis of patients with colorectal cancer

As the second leading cause of cancer worldwide, colorectal cancer (CRC) is associated with a poor prognosis. Although recent studies have explored prognostic markers in patients with CRC, whether tissue microbes carry prognostic information remains unknown. Here, by assessing the colorectal tissue microbes of 533 CRC patients, we found that Proteobacteria (43.5%), Firmicutes (25.3%), and Actinobacteria (23.0%) dominated the colorectal tissue microbiota, which was different from the gut microbiota. Moreover, two clear clusters were obtained by clustering based on the tissue microbes across all samples. By comparison, the relative abundances of Proteobacteria and Bacteroidetes in cluster 1 were significantly higher than those in cluster 2; while compared with cluster 1, Firmicutes and Actinobacteria were more abundant in cluster 2. In addition, the Firmicutes/Bacteroidetes ratios in cluster 1 were significantly lower than those in cluster 2. Further, compared with cluster 2, patients in cluster 1 had relatively poor survival (Log-rank test, p = 0.0067). By correlating tissue microbes with patient survival, we found that the relative abundance of dominant phyla, including Proteobacteria, Firmicutes, and Bacteroidetes, was significantly associated with survival in CRC patients. Besides, the co-occurrence network of tissue microbes at the phylum level of cluster 2 was more complicated than that of cluster 1. Lastly, we detected some pathogenic bacteria enriched in cluster 1 that promote the development of CRC, thus leading to poor survival. In contrast, cluster 2 showed significant increases in the abundance of some probiotics and genera that resist cancer development. Altogether, this study provides the first evidence that the tissue microbiome of CRC patients carries prognostic information and can help design approaches for clinically evaluating the survival of CRC patients.

miR-130a-Mediated KLF3 Can Inhibit the Growth of Lung Cancer Cells

Background

The role of microRNA (miR) in tumors has been reported in numerous articles. Previous studies have found that miR-130a is low expressed in lung cancer, but the related mechanism has not been fully elucidated. This study mainly explores the mechanism of miR-130a in lung cancer, so as to provide potential therapeutic targets for clinical applications.

Methods

Quantitative real-time polymerase chain reaction (qRT-PCR) was used to detect the expression of miR-130a and KLF3 in the tissues of lung cancer patients. The miR-130a-mimics and miR-130a-inhibit were constructed. Cell proliferation, invasion, migration and apoptosis were determined by CCK-8, transwell, scratch test and flow cytometry. Western Blot was used to determine the expression of KLF3 protein in cells, and the dual-luciferase reporter to determine the relationship between KLF3 and miR-130a.

Results

miR-130a shows low expression in NSCLC patients, while KLF3 shows high expression, exhibiting a negative correlation. The 5-year survival rate of patients with low miR-130a expression and high KLF3 expression was reduced. Cox regression analysis showed that miR-130a was an independent prognostic factor for NSCLC patients. The dual-luciferase reporter revealed that miR-130a bound to KLF3 in a targeted manner, and cell experiments showed that miR-130a could inhibit the growth of lung cancer cells by regulating the expression of KLF3.

Conclusion

miR-130a shows low expression in lung cancer and predicts a poor prognosis. In addition, up-regulation of miR-130a can down-regulate KLF3 and inhibit the growth of lung cancer.

Differentiation between suture recurrence and suture granuloma after pulmonary resection for lung cancer by diffusion-weighted magnetic resonance imaging or FDG-PET / CT

There has been no publication which supports the usefulness of DWI differentiating for suture recurrence and suture granuloma after resection for lung cancer. We presented efficacy of DWI or FDG-PET/CT for an assessment of suture lesions after resection for lung cancer. Thirteen suture recurrences and 15 suture granulomas were examined. There were 24 adenocarcinomas and 4 squamous cell carcinomas, and 26 partial resections and 2 segmentectomies. The period of time (907±907 days) between surgery and suture recurrence was not significantly longer than that (546±547 days) between surgery and suture granuloma. Diffusion detectability scores (a 5-point scale) of suture recurrences was significantly higher than that of suture granulomas. The ADC value (1.35±0.24 × 10^-3mm²/sec) of suture recurrences was significantly lower than that (1.85±0.60 × 10^-3mm²/sec) of suture granulomas. The SUVmax (6.1 ± 5.0) of suture recurrences was not significantly higher than that (4.2 ± 2.5) of suture granulmas. The sensitivity of 85% (11/13) with DWI was not significantly higher than 69% (9/13) with FDG-PET/CT for suture recurrences. The specificity of 73% (11/15) with DWI was not significantly higher than the 60% (9/15) with FDG-PET/CT for suture granulomas. The accuracy of 79% (22/28) with DWI was not significantly higher than that of 64% (18/28) with FDG-PET/CT for suture recurrences and granulomas. DWI can differentiate suture granuloma from suture recurrence after resection of lung cancer. DWI is more useful than FDG-PET/CT for the differentiation between suture recurrence and suture granuloma after resection for lung cancer.

Diagnostic significance of apparent diffusion coefficient values with diffusion weighted MRI in breast cancer: a meta- analysis

AIMS

Apparent diffusion coefficient (ADC) values of nodes in diffusion-weighted imaging (DWI) are widely used in differentiating metastatic from non-metastatic lymph nodes. The purpose of this meta-analysis was to demonstrate whether DWI could contribute to the precise diagnosis of breast cancer (BC) with and without lymph node metastasis (LNM).

MATERIALS AND METHODS

English and Chinese electronic databases were searched for relevant studies followed by a comprehensive literature search. Two reviewers independently assessed the methodological quality of the included trials based on the quality assessment of diagnostic accuracy studies (QUADAS). Summary odds ratios (ORs) and corresponding 95% confidence intervals (95% CIs) were calculated.

RESULTS

Final analysis of 624 BC subjects (patients with LNM = 254, patients without LNM = 370) were incorporated into the current meta-analysis from 9 eligible cohort studies. Combined ORs of ADCs suggested that ADC values in BC patients without LNM were higher than in patients with LNM (OR=0.56, 95%CI: 0.11-1.01, p=0.015). Subgroup analysis stratified by country indicated a low ADC value in BC patients with LNM rather than those without LNM among Chinese (OR=1.27, 95%CI: 0.89-1.66, p<0.001), Italians (OR=0.75, 95%CI: 0.13-1.38, p=0.018), and Egyptians (OR=1.27, 95%CI: 0.71-1.84, p<0.001). The findings of subgroup analysis by MRI machine type revealed that ADC values from diffusion MRI may be potential diagnostic indicators for BC using Non-Philips 1.5T (OR=1.10, 95%CI: 0.84-1.36, p<0.001).

CONCLUSIONS

The main findings of our meta-analysis demonstrated that increased signal intensity on DWI and decreased signals on ADC are helpful in diagnosis of BC patients with or without LNM. DWI could therefore be an important imaging investigation in patients suspected of BC.